PROJECT SUMMARY The outcomes of our actions are seldom certain. Individuals vary substantially in their attitudes towards uncertainty: some seek it, while others avoid it at all costs. These individual differences are important, because they largely shape who we are, and because they are linked to variability in a host of maladaptive behaviors and mental disorders. The underlying causes for these individual differences, however, are poorly understood. To unravel the neural mechanisms of individual differences in behavior under uncertainty we must obtain a detailed understanding of that behavior. We do know that uncertainty attitudes are context dependent. For example, attitudes towards uncertain gains are not strongly correlated with attitudes towards uncertain losses. This suggests that uncertainty attitudes result from interactions between several cognitive and motivational processes. The proposed studies will test the contribution of three basic processes to uncertainty attitudes: the individual's ability to reduce uncertainty by learning from feedback, her sensitivity to rewards, and her sensitivity to punishments. We hypothesize that posterior parietal mechanisms play an important role in shaping individual uncertainty attitudes based on these cognitive and motivational processes. We plan to test these hypotheses in a group of 200 men and women from the general population, using three behavioral tasks in conjunction with structural and functional MRI. To ensure that our behavioral measures are independent of each other, we will estimate risk and ambiguity attitudes, in reward and punishment domains, in the absence of learning, and examine both learning and anticipation of rewards and punishments in the absence of decision making. The expected outcomes of the proposed work are twofold. At the behavioral level, we expect to obtain a detailed understanding of the role of learning, as well as reward and punishment processing, in individual uncertainty attitudes. At the neural level, we expect to identify structural features and functional mechanisms that underlie these individual differences, thus providing computational constraints on these processes. We expect these findings to guide the future development of individually-tailored decision aids and behavioral interventions for individuals with maladaptive decision processes.